Assessment of Vaccines
Slides: https://www.andreashandel.com/presentations/
2023-10-30
Vaccines are pretty good
![]()
xkcd.com
Evaluation of vaccines
How do we determine if vaccines are good?
- Safety
- Immunogenicity
- Efficacy/Effectiveness
- Cost-effectiveness
Vaccine Development
![]()
Knipe et al Science 2020
Outcomes of interest
Vaccines (partially) protect those who receive them (direct/individual effect):
- Reduction in risk of infection/symptoms/hospitalization/death.
- Reduction in strength of symptoms.
Outcomes of interest
Vaccines (partially) protect those who receive them (direct/individual effect):
- Reduction in risk of infection/symptoms/hospitalization/death.
- Reduction in strength of symptoms.
Vaccines can also protect non-vaccinated contacts (indirect effect).
- Reduction of susceptibles in the population leads to overall reduced spread (contagion effect).
- Reduction of infectiousness/transmission potential leads to reduced spread (infectiousness effect).
See Halloran & Hudgens 2016 CER and references therein.
Indirect effect example
- Vaccine 1 reduces risk of clinical infection by 70%, reduces infectiousness by 30%.
- Vaccine 2 reduces risk of clinical infection by 30%, reduces infectiousness by 70%.
![]()
Gallagher et al, medRxiv 2020
Ways to evaluate vaccine impact
Measure it:
- Challenge studies
- Clinical trials
- Observational studies
Estimate it:
Measuring vaccine impact
Challenge studies
- One group receives the vaccine, the other placebo.
- Both groups are challenged with the pathogen under consideration.
- Measures vaccine efficacy (VE).
- Well-controlled, can use small(ish) sample size.
- Somewhat unrealistic (e.g., high challenge doses).
- Direct effect only.
- Sometimes not feasible/ethical.
Clinical trials
- One group receives the vaccine, the other placebo.
- Groups are followed and outcome (infection/disease/etc.) recorded.
- Measures vaccine efficacy (VE).
- Good balance between controlled and real-world setting.
- Usually needed for FDA approval.
- Only works if infections are high (not good for emerging pathogens).
- Can measure direct and indirect effects (but usually only direct).
- Expensive.
Observational studies
- Taking vaccine is up to individuals (so must be licensed).
- Cohort and case-control (e.g., test-negative) design.
- Measures vaccine effectiveness (VE).
- Most “real”, least controlled.
- Can lead to biased estimates.
- Can measure direct and indirect effects.
- Can be fairly inexpensive.
Test-negative design
![]()
Sullivan et al 2014 Exp Rev Vac
Measuring vaccine impact - summary
- Different study designs are available/useful.
- As you learned from the Halloran & Hudgens paper, because of dependent happenings, designing and analyzing vaccine studies to properly capture all vaccine effects can be tricky.
- Generally, a “classical” convincing phase 3 clinical trial is required to get approval (but see e.g., Ebola vaccine, H5N1 influenza vaccine).
- Measuring actual outcomes is always expensive and time-consuming, sometimes not feasible (e.g., SARS-CoV-3 or H5N1 influenza vaccines).
Estimating vaccine impact
![]()
xkcd.com
Correlates of protection (CoP)
- Determining an immunological quantity that correlates with protection can make vaccine assessment easier.
- Finding correlates of protection (for vaccines) is very valuable (but can be tricky).
![]()
xkcd.com
Vaccine CoP terminology
- It’s a mess.
- Some individuals (e.g., Plotkin) mean by “correlate” a mechanistic/causal entity.
- Some individuals mean by “correlate” something that correlates and might or might not be mechanistic/causal.
- Other terms are used by some to try to be clearer (e.g., surrogate, mechanistic CoP). See e.g. Plotkin & Gilbert 2012 CID.
- Protection is also often not clearly defined.
Correlates of protection
- An “absolute correlate” (a la Plotkin) does not exist.
- Levels at which a CoP leads to protection depend on pathogen, host, outcome, etc.
CoP - SARS-CoV-2 Example
![]()
Khoury et al 2021 Nat Med
CoP - SARS-CoV-2 Example
![]()
Khoury et al 2021 Nat Med
CoP - Influenza Example
![]()
Coudeville et al 2010 BMC MRM
CoP - Influenza Example
CoP - Influenza Example
CoP - Influenza Example
CoP - Influenza Example
CoP - Influenza Example
CoP - Influenza Example
![]()
Age Group 50-64
CoP - Influenza Example
![]()
Age Group 65+
CoP - Influenza Example
![]()
Age Group 18-49
Estimating vaccine impact - summary
- Using CoP can speed up approval process.
- CoP can depend on details of vaccine (e.g., LAIV vs. IIV) and hosts (e.g., children vs. adults).
- A full mechanistic understanding of
vaccine -> immune response -> protection
is still lacking for any vaccine (afaik).
Keep going?
![]()
Image by Aline Dassel/Pixabay